Mean dna copy number of chromosomal regions is of prognostic significance in cancer

ABSTRACT

Methods for predicting a disease free time interval (DFI) for a cancer patient under consideration for initial or further chemotherapy treatment are disclosed. The methods include obtaining a biological sample from a patient and detecting a copy number of chromosome region A1 and/or C2. The mean copy number per cell is correlated with a DFI for the subject. The chemotherapy can include doxorubicin and/or L-asparaginase treatment. Also provided are kits for predicting DFI in a subject with cancer and computer readable storage media for performing the presently disclosed methods.

CROSS REFERENCE TO RELATED APPLICATIONS

The presently disclosed subject matter claims the benefit of U.S.Provisional Patent Application Ser. No. 61/284,164, filed Dec. 14, 2009,the disclosure of which is incorporated herein by reference in itsentirety.

TECHNICAL FIELD

The presently disclosed subject matter relates generally to methods andtests for analyzing recurrent DNA copy number changes in tumor tissuesamples from cancer subjects. Copy number is predictive of response totherapy, time of first remission, and in some cases overall survival.

BACKGROUND

It is estimated that there over 4,000,000 cases of canine cancerdiagnosed in the United States of America each year, of which up to onequarter are represented by canine lymphoma. While the total number ofdogs that are treated for lymphoma is not clear, a conservative estimateis that in the United States of America alone approximately 7,000-10,000dogs per year are treated with chemotherapy (typically using protocolsthat include doxorubicin) for lymphoma. The typical cost of thistreatment is about $4,000-6,000, resulting in an annual treatment costin the USA of approximately $30,000,000-$60,000,000.

The vast majority of owners do not treat their dogs for their lymphoma,however. Discussions with veterinary oncologists suggest that one reasonfor this is the cost of treatment, while another common reason is the“cost versus unknown outcome”. A widely used treatment protocol termed“UW-25” is reported to provide up to 90% chance of remission for amedian survival of nine months. However, individual remissions can varyfrom weeks to years, and as a result, the availability of a test thatcan more accurately predict the duration of remission following therapywould be of great value to clinicians and clients in the decisionprocess.

If such a predictive test were available, many more owners mightconsider treating their dog for lymphoma, particularly if they weregiven an accurate predictor of how their dog will respond to therapy,assuming that such a test could be offered at an affordable level ofexpense. While some owners still would not be in a position to affordthe cost of chemotherapy, regardless of possible outcome, there islikely a large number who would be more willing to treat their dogs ifthey knew that the chance of their pet surviving for, For example, atleast a year, was 90-95% or greater. On this basis, the number ofcandidates that could be considered as a potential beneficiary of a testthat would predict time to remission might be substantially higher than10,000 per year.

Lymphoma is the most common life-threatening cancer in dogs, accountingfor up to 24% of all canine malignancies and over 80% of all caninehematopoietic cancers. As in humans, canine lymphoma is a spontaneousmalignancy and is generally a disease of middle-aged to older dogs thataffects a wide range of breeds.

Untreated cases of canine lymphoma rarely survive beyond three monthspost-diagnosis, but a large proportion (up to 90%) of canine lymphomasare generally responsive to standards of care using either single agentor multi-agent chemotherapy, increasing both the length and quality ofan affected dog's life. Among treated cases receiving the same initialdiagnosis, however, there is considerable variation in the extent ofresponse to therapy and overall survival time. This indicates that thereis a need to develop more refined modes of classification that are ofprognostic significance. At the present time, however, there is noavailable approach to accurately predict response to chemotherapy ofdogs diagnosed with lymphoma.

The PATHVYSION™ HER-2 DNA Probe Kit (Abbott Laboratories, Des Plaines,Ill., United States of America) is designed to detect amplification ofthe HER-2/neu gene via fluorescence in situ hybridization (FISH) informalin-fixed, paraffin-embedded human breast cancer tissue specimens.The kit uses the relative copy number of the HER-2 gene to help predicttime to remission of the breast cancer.

Described herein is a novel test has been developed for a cancer. Thetest provides clinicians with the ability to predict with a degree ofstatistical probability how long before their lymphoma patients willlikely enter first remission when treated with a standard of caretherapy. There is immediate significance to the veterinary market andpredictive potential of the chromosomal regions defined in caninelymphoma in human cancer patients. These regions can inform humanoncologists of the likely remission period for human cancer patients.

SUMMARY

This Summary lists several embodiments of the presently disclosedsubject matter, and in many cases lists variations and permutations ofthese embodiments. This Summary is merely exemplary of the numerous andvaried embodiments. Mention of one or more representative features of agiven embodiment is likewise exemplary. Such an embodiment can typicallyexist with or without the feature(s) mentioned; likewise, those featurescan be applied to other embodiments of the presently disclosed subjectmatter, whether listed in this Summary or not. To avoid excessiverepetition, this Summary does not list or suggest all possiblecombinations of such features.

The presently disclosed subject matter provides in some embodimentsmethods for predicting the disease free time interval for cancerpatients, under consideration for initial or further chemotherapytreatment. In some embodiments, the methods comprise obtaining abiological sample from a patient and detecting the copy number ofchromosome region A1 as defined herein. The biological sample cancontain a number of cells (i.e. one or more cells). A mean copy numbervalue of chromosome region A1 is in some embodiments determined bydividing the total copy number by the number of cells in the sample. Themean copy number is then correlated with time of first remission.

In some embodiments, the methods include embodiments wherein the patienthas lymphoma, such as but not limited to non-Hodgkin's lymphoma.

In some embodiments, the patient is a canine.

The presently claimed subject matter also provides in some embodimentsmethods wherein the biological sample comprises a biopsy from a patient.The biopsy can be taken from any tissue desired and can comprise tumorand/or lymph node cells.

The presently disclosed methods include embodiments wherein thedetecting a copy number of chromosome region A1 comprises contacting thesample with a probe able to detect the presence of chromosome region A1under conditions sufficient to enable hybridization of the probe tochromosome region A1. The probe can be fluorescently labeled.

In some embodiments, the contacting the biological sample can comprisefluorescence in situ hybridization (FISH) analysis. In some embodiments,the contacting the sample can comprise polymerase chain reaction (PCR)analysis.

In some embodiments, the methods comprise determining the disease freeinterval (DFI) by substituting the mean copy number of chromosome regionA1 per cell value into Formula A, wherein Formula A is:

DFI=374.1685×(mean copy number value for A1)−438.7572 days

In some embodiments, the methods further comprise, before making therisk correlation, detecting the copy number of chromosome region C2. Amean copy number value of chromosome region C2 is in some embodimentsdetermined by dividing the total copy number of chromosome region C2 bythe number of cells in the sample. The detecting the copy number ofchromosome region C2 can comprise contacting the sample with a probeable to detect the presence of chromosome region C2 under conditionssufficient to enable hybridization of the probe to chromosome region C2.

In some embodiments, the methods further comprise determining thedisease free interval (DFI) by substituting the mean copy number ofchromosome region A1 and the mean copy number of chromosome region C2values into Formula AC, wherein Formula AC is:

DFI=367.5094×(mean copy number value for A1)+228.2709×(mean copy numbervalue for C2)−839.22 days

In some embodiments, there is a positive correlation between mean copynumber of chromosome regions A1 and C2 and duration of disease free timeinterval.

The presently disclosed subject matter also provides in some embodimentstesting kits for predicting disease free time interval in a patientunder consideration for initial or further chemotherapy treatment. Thekit comprises in some embodiments a probe able to detect the chromosomeregion A1.

In some embodiments, the testing kits further comprises a probe able todetect chromosome region C2.

In some embodiments, a computer readable medium is provided which hasstored thereon computer executable instructions that when executed by aprocessor of a computer control the computer to perform steps comprisinganalyzing a mean copy number from chromosome region A1 and/or chromosomeregion C2 from a biological sample and outputting a predicted DFI. Theprocessor of the computer can employ Formula I and/or II to compute DFI.

It is thus an object of the presently disclosed subject matter toprovide methods for predicting the duration of first remission forcancer patients under consideration for initial or further chemotherapy,including chemotherapy comprising doxorubicin or further comprisingasparaginase.

An object of the presently disclosed subject matter having been statedhereinabove, and which is achieved in whole or in part by the presentlydisclosed subject matter, other objects will become evident as thedescription proceeds when taken in connection with the accompanyingdrawings and non-limiting examples as best described herein below.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram of an exemplary protocol that can be employed forperforming comparative genome hybridization (CGH) analysis on an array.

FIG. 2 is a graph depicting the frequency of DNA copy number increases(gain) and decreases (loss) observed across a collection of over 200cases of canine lymphoma. The x-axis represents positions along the 38pairs of autosomes in the canine genome (CFA1-38).

FIG. 3 is a bar graph showing the number and circumstances under whichindividual patients (n=322) left a study disclosed herein.

FIG. 4 is a bar graph showing the distribution of the 322 patients withregard to their Disease Free Interval (DFI). Darker bars represent 90day intervals and lighter bars represent 30 day intervals.

FIG. 5 is an image of biopsied tumor tissue. Cases from the trialdisclosed herein were coded and provided in a blind manner. Each of thecases was reviewed to determine the presence of large regions ofnon-neoplastic tissues (e.g., skin), and these were noted on thehematoxylin and eosin stain (H+E).

FIG. 6 is a series of images showing an exemplary procedure that can beused for isolation and characterization of tumor cells. To obtain asufficient number of intact nuclei, 25 micron slices ofparaffin-embedded tissue, which are thicker than one cell, can beremoved from each tissue block, and any large regions of non-neoplastictissue can be macro-dissected away. The remainder of the slice can beput into a microfuge tube and the tissue extracted with xylene. Pepsincan be used to generate a cell suspension, which can then be fixed inreadiness to make preparations on glass slides.

FIG. 7 is a diagram showing an exemplary approach that can be used toassess copy number. Cells from several cases can be applied to a singleslide. The slide can be masked with rubber cement to ensure no crosscontamination of each individual cell preparation. This approach canallow for a greater level of inter-case consistency and minimized probevariability.

FIG. 8 is a diagram depicting a case of multi-color, multi-casehybridization. The cases on each slide of FIG. 7 were used as templatesfor multicolor fluorescence in situ hybridization (FISH), where thecells were exposed to a common hybridization mix containingfluorescently labeled DNA representing the regions being evaluated forgenomic copy number. The signals generated by the hybridization werethen determined using multi-plane fluorescence microscopy, whichproduced images such as the cell depicted in the top right panel of FIG.8. This single cell was from a canine lymphoma patient that had beenhybridized with five differentially labeled probes. Since the fivefluorophores employed were spectrally discrete, they were easy todistinguish as red, orange, green, aqua, and purple spots in the actualphotomicrograph. The cell was also counterstained with4′,6-diamidino-2-phenylindole (DAPI), a fluorescent dye that binds toDNA and stains nuclei blue. In a non-neoplastic cell, the copy number ofeach locus was expected to be n=2. In this lymphoma cell, the copynumber of the red (uncircled spots identified by the thick blackarrows), orange (uncircled spots identified by the thin black arrows),and purple (uncircled spots identified by the thick white arrows) probeswas two, while the green (circled spots identified by the thick whitearrows) and aqua (circled spots identified by the thin white arrows)probes both had three copies. These two probes represented regions ofcanine chromosomes 13 and 31, respectively.

FIG. 9 is a series of images showing the technical challenges that canarise when using archival samples. The cell in the top image was a cellfrom a fresh lymph node biopsy. Note the sharp dots indicative ofdetected chromsomoes. The four cells in the bottom images were eachsingle plane images of data obtained from cells isolated from a formalinfixed paraffin block, showing high levels of background fluorescence.

FIGS. 10A-10E shows a diagram and a photomicrograph, respectively, ofthe development of BAC contigs to increase the signal:noise ratio (FIG.10A) and improve scoring of BAC clones (FIGS. 10B-10E). The probes usedin conventional FISH were generally single BAC clones that each spannedapproximately 200 kilobases (kb) of the canine genome (e.g., the thickblack line identified with a single asterisk to its right in FIG. 10A).These probes generally provided a small but easily scored signal whenused in FISH of non-fixed cells (see FIG. 10B), but produced a highbackground when used with fixed cells (see FIG. 10D). When overlappingBAC clones were selected (thick lines in FIG. 10A identified with doubleasterisks) then pooled and labeled with a fluorochrome, the resultingsignal was much larger in unfixed cells (compare signal size in FIG. 10Cto that in FIG. 10B). In fixed nuclei, this increase in signal size(FIG. 10E) allowed also for reduction in background noise (compare FIG.10E to FIG. 10D) and permitted scoring with confidence. As with existingcytogenetic testing, there was a small frequency (up to 3%) of “normal”cells, both from fixed or unfixed tissues, that had a copy number ofn=1, though the frequency of “normal” cells with n>2 was zero.

FIG. 11 is an image showing single locus probe (SLP) analysis of 10probes (in two sets of five probes, one each in the left panel and inthe right panel) on unfixed non-neoplastic lymphocytes. No neoplasticcells are shown. The copy number is n=2 for all 10 probe pools.

FIG. 12 is an image depicting SLP analyses of the same panel of 10probes in FISH of unfixed lymphoma cells. In the left panel the copynumber of chromosome regions A1, A3, and C1 is n=3, and in the rightpanel the copy number of B2 is n=3. As with non-neoplastic cells, inunfixed neoplastic cells, these ten loci were routinely evaluated in tworeactions, each with five differentially labeled BAC pools.

FIG. 13 is a series of images depicting three color SLP analyses of ninefixed non-neoplastic lymph node cells. For each panel, arrow connectedat their bases point to signals of the same color in the originalphotomicrograph. Single arrows indicate signals that were present inonly one copy in the original photomicrograph. Seven of these cellspresented with signals for all three probes that were able to be scoredand the score of each of the three probes is indicated. Two of the cells(boxed; lower middle and right) are shown as examples of cells thatproduced data that were not scorable for the green signal (triple arrowidentified with a “?”) or any of the three signals (right). As withnon-fixed cells, scores of fixed cells indicated a frequency of n=1 forup to 3% of cells counted.

FIG. 14 is an example of four loci, multicolor FISH analysis of canineinterphase nuclei. The left panel is an image of a control,non-neoplastic cell showing two copies of each of the four loci beingevaluated for chromosome regions A1 (red in the originalphotomicrograph), A2 (orange in the original photomicrograph), C2(purple in the original photomicrograph), and C3 (green in the originalphotomicrograph). The right panel is an image of a neoplastic nucleusfrom a canine lymphoma biopsy specimen probed simultaneously with thesame four probes. In this cell, though there were two copies of thelocus labeled with the green fluorophore in the original photomicrograph(labeled C3 in this panel), there were three copies each of the probeslabeled with the red fluorophore in the original photomicrograph(labeled A1) and purple fluorophore in the original photomicrograph(labeled C2). There were no retained copies of the marker labeled withthe orange fluorophore in the original photomicrograph (probe A2).Counts were made from >50 cells and the mean copy number of each locuswas determined and collated.

FIG. 15 is a block diagram of a computer, including a prediction of DFImodule (505), suitable for use in performing the functions describedherein.

DETAILED DESCRIPTION I. Definitions

All technical and scientific terms used herein, unless otherwise definedbelow, are intended to have the same meaning as commonly understood byone of ordinary skill in the art. References to techniques employedherein are intended to refer to the techniques as commonly understood inthe art, including variations on those techniques or substitutions ofequivalent techniques that would be apparent to one of skill in the art.While the following terms are believed to be well understood by one ofordinary skill in the art, the following definitions are set forth tofacilitate explanation of the presently disclosed subject matter.

All references listed herein, including but not limited to patents,patent application publications, journal articles, and database entries(e.g., GENBANK® database entries including all annotations andreferences cited therein) are incorporated herein by reference to theextent that they supplement, explain, provide a background for, or teachmethodology, techniques, and/or compositions employed herein.

Following long-standing patent law convention, the terms “a”, “an”, and“the” mean “one or more” when used in this application, including theclaims. Thus, the phrase “a cell” refers to one or more cells, unlessthe context clearly indicates otherwise.

As used herein, the term “and/or” when used in the context of a list ofentities, refers to the entities being present singly or in combination.Thus, for example, the phrase “A, B, C, and/or D” includes A, B, C, andD individually, but also includes any and all combinations andsubcombinations of A, B, C, and D.

The term “comprising”, which is synonymous with “including”,“containing”, and “characterized by”, is inclusive or open-ended anddoes not exclude additional, unrecited elements and/or method steps.“Comprising” is a term of art that means that the named elements and/orsteps are present, but that other elements and/or steps can be added andstill fall within the scope of the relevant subject matter.

As used herein, the phrase “consisting of” excludes any element, step,and/or ingredient not specifically recited. For example, when the phrase“consists of” appears in a clause of the body of a claim, rather thanimmediately following the preamble, it limits only the element set forthin that clause; other elements are not excluded from the claim as awhole.

As used herein, the phrase “consisting essentially of” limits the scopeof the related disclosure or claim to the specified materials and/orsteps, plus those that do not materially affect the basic and novelcharacteristic(s) of the disclosed and/or claimed subject matter. Forexample, the presently disclosed subject matter in some embodiments can“consist essentially of” determining a copy number of a chromosomeregion in cells obtained from a subject, which means that the recitedchromosome region i the only chromosome region for which a copy numberis determined. It is noted, however, that a copy number for variouspositive and/or negative control chromosome regions can also bedetermined, for example, to standardize and/or normalize the copy numberof the selected chromosome region (if desired).

With respect to the terms “comprising”, “consisting essentially of”, and“consisting of”, where one of these three terms is used herein, thepresently disclosed and claimed subject matter can include the use ofeither of the other two terms. For example, the presently disclosedsubject matter relates in some embodiments to methods that comprisedetermining a copy number of a chromosome region identified herein asA1. It is understood that the presently disclosed subject matter thusalso encompasses methods that consisten essentially of determining acopy number of a chromosome region identified herein as A; as well asmethods that consist of determining a copy number of a chromosome regionidentified herein as A1.

The term “subject” as used herein refers to a member of any invertebrateor vertebrate species. Accordingly, the term “subject” is intended toencompass any member of the Kingdom Animalia including, but not limitedto the phylum Chordata (i.e., members of Classes Osteichythyes (bonyfish), Amphibia (amphibians), Reptilia (reptiles), Ayes (birds), andMammalia (mammals)), and all Orders and Families encompassed therein. Insome embodiments, the presently disclosed subject matter relates tocanine subjects. In some embodiments, the presently disclosed subjectmatter relates to human subjects.

Similarly, all genes, gene names, and gene products disclosed herein areintended to correspond to orthologs from any species for which thecompositions and methods disclosed herein are applicable. Thus, theterms include, but are not limited to genes and gene products fromcanines and/or humans. It is understood that when a gene or gene productfrom a particular species is disclosed, this disclosure is intended tobe exemplary only, and is not to be interpreted as a limitation unlessthe context in which it appears clearly indicates. Thus, for example,the genes and/or gene products disclosed herein are also intended toencompass homologous genes and gene products from other animalsincluding, but not limited to other mammals, fish, amphibians, reptiles,and birds.

The various embodiments of the presently disclosed subject matter areparticularly useful for warm-blooded vertebrates. Thus, the presentlydisclosed subject matter concerns mammals and birds. More particularlyprovided is the use of the methods and compositions of the presentlydisclosed subject matter on mammals such as humans and other primates,as well as those mammals of importance due to being endangered (such asSiberian tigers), of economic importance (animals raised on farms forconsumption by humans) and/or social importance (animals kept as pets orin zoos) to humans, for instance, carnivores other than humans (such ascats and dogs), swine (pigs, hogs, and wild boars), ruminants (such ascattle, oxen, sheep, giraffes, deer, goats, bison, and camels), rodents(such as mice, rats, and rabbits), marsupials, and horses. Also providedis the use of the disclosed methods and compositions on birds, includingthose kinds of birds that are endangered, kept in zoos, as well as fowl,and more particularly domesticated fowl, e.g., poultry, such as turkeys,chickens, ducks, geese, guinea fowl, and the like, as they are also ofeconomic importance to humans. Thus, also provided is the application ofthe methods and compositions of the presently disclosed subject matterto livestock, including but not limited to domesticated swine (pigs andhogs), ruminants, horses, poultry, and the like.

The term “about”, as used herein when referring to a measurable valuesuch as an amount of weight, time, dose, etc., is meant to encompassvariations of in some embodiments ±20%, in some embodiments ±10%, insome embodiments ±5%, in some embodiments ±1%, and in some embodiments±0.1% from the specified amount, as such variations are appropriate toperform the disclosed methods and/or to employ the presently disclosedarrays.

The term “isolated”, as used in the context of a nucleic acid orpolypeptide (including, for example, a nucleotide sequence, apolypeptide, and/or a peptide), indicates that the nucleic acid orpolypeptide exists apart from its native environment. An isolatednucleic acid or polypeptide can exist in a purified form or can exist ina non-native environment.

Further, as used for example in the context of a cell, nucleic acid,polypeptide, or peptide, the term “isolated” indicates that the cell,nucleic acid, polypeptide, or peptide exists apart from its nativeenvironment. In some embodiments, “isolated” refers to a physicalisolation, meaning that the cell, nucleic acid, polypeptide, or peptidehas been removed from its native environment (e.g., from a subject).

The terms “nucleic acid molecule” and “nucleic acid” refer todeoxyribonucleotides, ribonucleotides, and polymers thereof, insingle-stranded or double-stranded form. Unless specifically limited,the term encompasses nucleic acids containing known analogues of naturalnucleotides that have similar properties as the reference naturalnucleic acid. The terms “nucleic acid molecule” and “nucleic acid” canalso be used in place of “gene”, “cDNA”, and “mRNA”. Nucleic acids canbe synthesized, or can be derived from any biological source, includingany organism.

As used herein, the terms “peptide” and “polypeptide” refer to polymersof at least two amino acids linked by peptide bonds. Typically,“peptides” are shorter than “polypeptides”, but unless the contextspecifically requires, these terms are used interchangeably herein.

As used herein, a cell, nucleic acid, or peptide exists in a “purifiedform” when it has been isolated away from some, most, or all componentsthat are present in its native environment, but also when the proportionof that cell, nucleic acid, or peptide in a preparation is greater thanwould be found in its native environment. As such, “purified” can referto cells, nucleic acids, and peptides that are free of all componentswith which they are naturally found in a subject, or are free from justa proportion thereof.

II. Methods and Compositions for Predicting Disease Free Interval (DFI)

Methods and compositions for predicting the duration of first remissionin patients diagnosed with lymphoma are disclosed. It has beendiscovered that mean DNA copy number of regions on canine chromosomes 1and 6 within a population of cancer cells are of prognostic significanceof disease free time interval in canine lymphoma patients. In someembodiments, the patients received chemotherapy protocols comprisingadministration of doxorubicin, which in further embodiments wassupplemented with L-asparaginase. The methods and compositions are basedon nucleic acid technology where nucleic acid probes are hybridized tocell samples and the number of copies of certain genetic regions isquantified. A genetic/cytogenetic test that can offer robustprognostication for canine lymphoma will replace staging in cancerdiagnoses.

Within a population of cells isolated from a lymph node biopsy specimen,the mean DNA copy number of selected regions of the canine genomeprovides statistically significant power to predict disease freeinterval of canine lymphoma patients treated with chemotherapy thatcomprises administration of doxorubicin, and which can includeL-asparaginase. In this context, disease free interval refers to thetime from diagnosis/initial chemotherapy treatment to the time that thepatient enters relapse, wherein relapse is a return of thesymptoms/signs of cancer after a period of remission. The presentlydisclosed subject matter has immediate implication for prognosticationin veterinary medicine. Use of this test will allow veterinarians toprovide a statistical probability of the likelihood of disease freeinterval in canine patients diagnosed with lymphoma who are treated withstandard of care. Further, within a population of cells obtained fromhuman lymphoma specimens, the mean DNA copy number of the correspondingregions of the human genome can similarly be associated with response totherapy for human lymphoma patients.

The presently disclosed subject matter provides methods, kits, andcomputer readable media for predicting the duration of first remissionin patients diagnosed with lymphoma, when treated with a therapy, suchas drug therapy, including but not limited to chemotherapy comprisingadministration of doxorubicin.

In some embodiments, a method for predicting the disease free timeinterval for a cancer patient under consideration for initial or furthertreatment comprises obtaining a biological sample from a patient anddetecting the mean copy number/cell of chromosome region A1. The patientcan be a treated cancer patient or a patient that is being consideredfor treatment. The sample can be contacted with a probe able to detectthe presence of A1 under conditions sufficient to enable hybridizationof the probe to A1. The number of copies of A1 is counted and thatnumber is divided by the number of cells in the sample. The sample cancontain one or more cells. A positive correlation has been shown betweenthe mean copy number per cell of region A1 and duration of 1^(st)remission. In some embodiments a mean copy number greater than two iscorrelated with an increase in time for DFI.

When the copy number of C2 is added to the model, the prognostic valueincreases. Again a positive correlation has been shown between the meancopy number per cell of region C2 and duration of 1^(st) remission.

The marker A1 was detected by a probe pool of four overlapping caninebacterial artificial chromosome (BAC) clones, which span a 796,156 bpregion of dog chromosome 1 (CFA1) between 116,839,835 bp and 117,635,991bp. The size of the region that presents with abnormal copy number canextend up to the full length of CFA1 (125,616,256 bp). Any marker thathybridizes exclusively to this region of CFA1 or any process that isable accurately to detect copy number of this region can serve as an A1marker. In addition our data indicate that the full length of CFA1 canbe involved and so any marker that hybridizes exclusively to any regionof CFA 1 or any process that is able accurately to detect copy number ofCFA 1 can serve as an A1 marker.

In the human genome, the region that is evolutionarily conserved withCFA1: 116,839,835-117,635,991 bp resides on human chromosome 19 in bandq13.2. This includes the region located at 43,452,745-44,221,900 bp in19q13.2. These boundaries can move as the genome is refined and so thesepositions represent the start and end positions of the human chromosomethat correspond to the CFA1 regions in the dog.

The marker C2 was detected by a probe pool of five overlapping BACclones which span an 861,477 bp region of dog chromosome 6 (CFA6)between 41,565,280 bp and 42,426,757 bp. The size of the region thatpresents with abnormal copy number extends up to the full length of CFA6(80,642,250 bp). Any marker that hybridizes exclusively to this regionof CFA6 or any process that is able accurately to detect copy number ofthis region can serve as a C2 marker. In addition our data indicate thatthe full length of CFA6 can be involved and so any marker thathybridizes exclusively to any region of CFA 6 or any process that isable accurately to detect copy number of CFA6 can serve as a C2 marker.

In the human genome, the region that is evolutionarily conserved withCFA6: nucleotides 41,565,280-42,426,757 resides on human chromosome 16in band p13.1. This includes the region located at nucleotides1,629,295-2,350,975 in HSA 16p13.1. These boundaries can move as thegenome is refined and so these positions represent the start and endpositions of the human chromosome that correspond to the CFA 6 regionsin the dog. The disease free interval can be predicted by any suitableapproach based on the copy number of A1 and/or C2, such as but notlimited to employing the representative formulas below using the onevariable, A1, Formula A model or the two variable, A1 and C2, Formula ACmodel.

DFI=374.1685×(mean copy number value for A1)−438.7572 days  Formula A

DFI=367.5094×(mean copy number value for A1)+228.2709×(mean copy numbervalue for C2)−839.22 days  Formula AC

The presently disclosed subject matter includes methods wherein thebiological sample can comprise tumor cells and/or lymph node cells froma patient, such as might be isolated by a biopsy. The patient can be adog. The methods include embodiments wherein the patient has beendiagnosed with lymphoma, including non-Hodgkin's lymphoma. The patientcan be treated or can be proposed for treatment with any therapy, suchas chemotherapy including but not limited to chemotherapy comprisingadministration of doxorubicin and/or L-asparaginase.

The methods and kits provided in accordance with the presently disclosedsubject matter can comprise employing one or more DNA probes that arefluorescently labeled to detect the presence of chromosomal regions. Thecontacting of the biological sample from a patient with the probe(s) cancomprise, for example, fluorescence in situ hybridization (FISH) orpolymerase chain reaction (PCR). Königshoff et al. (Clinical Chem 49(2):219-229 (2003)) describe methods of quantification of copy number usingReal-Time PCR in a study of HER-2/neu in breast cancer tissue.

The presently disclosed subject matter also provides a testing kit forpredicting disease free time interval in a patient treated or proposedfor treatment with any therapy, such as chemotherapy including but notlimited to chemotherapy comprising administration of doxorubicin and/orL-asparaginase. In some embodiments, the kit comprises a probe(s) ableto detect the chromosome regions A1, C2, and/or A1 and C2

In some embodiments a testing kit is based on assessing mean DNA copynumber for chromosome regions A1, C2, and/or A1 and C2 usingfluorescence in situ hybridization (FISH) analysis of cells derived fromlymph node specimens. Formulas A and/or AC can be employed to predictDFI, as non-limiting examples.

III. Comparative Genomic Hybridization (CGH) Analysis

Comparative genomic hybridization (CGH) is a technique by whichdifferences in copy number of various genomic loci between two sets ofsamples (e.g., a normal tissue sample and a tissue sample comprisingcancer cells) can be determined (see Kallioniemi et al. (1992)Comparative Genomic Hybridization for Molecular Cytogenetic Analysis ofSolid Tumors, Science 258:818-821; Kallioniemi et al. (1994) Detectionand mapping of amplified DNA sequences in breast cancer by comparativegenomic hybridization, Proc Nat Aced Sci USA 91:2156-2160). A basicstrategy for CGH analysis is depicted in FIG. 1. In CGH, DNA from afirst tissue (i.e., a tumor or other cancer) and from a second tissue(e.g., normal tissue from the same species or individual) are labeledwith different detectable moieties (e.g., fluorescent labels). Aftermixing the first and second DNA samples with unlabeled C₀t1 DNA DNA thathas been enriched in repetitive DNA, typically from the same species asfrom which the first and second DNA samples have been isolated), themixture is hybridized to a solid support (e.g., a microarray) containingdefined DNA probes representing chromosome regions for which copynumbers are to be assayed. The fluorescence at the various locations onthe solid support are then detected, thereby providing information withrespect to the copy numbers of the carious chromosome regions assayed inthe first vs. in the second DNA samples.

Cytogenetic changes in a variety of canine cancers were analyzed bydeveloping a custom, genome-wide, assembly integrated canine BAC array(1 megabase (Mb) resolution) for evaluation of recurrent DNA copy numberchanges. Canine cancer patients were simultaneously recruited andevaluated for clinical follow-up. The approach identified a series ofrecurrent DNA copy number changes in a variety of canine cancers (e.g.,lymphoma, osteosarcoma, intracranial malignancies, soft tissue sarcomas,etc.).

Several of these recurrent changes are evolutionarily conserved with thecorresponding human cancer. Gene discovery, treatment, and prognosis inthe dog can thus be translate to corresponding human cancers.

Using the treatment regime and clinical outcome permitted identificationof associations between cytogenetic changes and response to therapy(time of first remission, overall survival).

Recurrent DNA copy number aberrations (CNAs) were identified in caninelymphoma, including copy number changes of regions of several dogchromosomes including chromosomes 1, 6, 11, 13, 14, 16, 18, 31, 37 and38. These are the ten (10) probes referred to in Example 2 herein below.The influences of these DNA CNAs were tested by looking at theirpresences in a panel of canine lymphoma patients with known outcomesfollowing treatments with standard of care chemotherapy. Tissue samplesfrom a study population were obtained from Colorado State University(CSU), Fort Collins, Colo., United States of America. The populationincluded 322 lymph node biopsy specimens. These specimens had beenobtained from a series of canine patients that were recruited as part ofmulticenter clinical trial. In the clinical trial, each of the dogs hadreceived single agent (doxorubicin) chemotherapy (supplemented withL-asparaginase) and then those dogs in remission at 15 weeks intotreatment (n=250) were further treated with either a “test” compound(n=125) or placebo (n=125) as part of a double blind placebo controlledtrial (described below).

Comparative genomic hybridization is a molecular cytogenetic techniquethat allows evaluation of DNA copy number changes on a genome-widelevel. Two custom BAC arrays were developed by selecting clones spacedevery 10 Mb and then every 1 Mb throughout the genome of the dog. Use ofthese arrays provided for the evaluation of a large number of caninetumor DNA samples and for the identification of regions of the genomethat were commonly altered in DNA copy number.

Cytogenetic evaluation (comparative genomic hybridization) of a smallnumber (n=25) of canine lymphomas identified a series of 10 recurrentDNA copy number changes. These changes remained evident when the numberof cases reached over 100, thus these 10 regions were selected for theirroles in prognosis of survival.

The most frequent whole chromosome copy number changes in caninelymphoma are gains of dog chromosomes 13 and 31. See FIG. 2. In additionthere are numerous smaller regions of gain and loss throughout thegenome. These smaller regions were assessed also to determine which wereassociated with prognosis.

The findings from the canine work are simultaneously translated tocorresponding regions of the human genome to investigate whether datafrom studies of the dog can benefit prognostic advances in humancancers.

IV. Computer Readable Storage Media

The presently disclosed subject matter also provides in some embodimentscomputer readable storage media such that the presently disclosed models(including, but not limited to Formulae A and AC) can be executed in acomputer program. Thus, in some embodiments, the subject matterdescribed herein for predicting DFI can be implemented in hardware,software, firmware, or any combination thereof. As such, the terms“function” or “module” as used herein refer to hardware, software,and/or firmware for implementing the feature being described.

Thus, in some embodiments the subject matter described herein forpredicting DFI can be implemented using a computer readable storagemedium having stored thereon executable instructions that when executedby the processor of a computer control the computer to perform steps ofanalyzing copy number from chromosome region A1, chromosome region C2,and/or chromosome regions A1 and C2, from a biological sample andoutputting a predicted DFI. The processor provided in the computerreadable medium can employ Formula A and/or Formula AC to compute DFI,as non-limiting examples.

FIG. 15 is a block diagram of a computer suitable for use in performingthe functions described herein. As depicted in FIG. 15, a system 500comprises a processor element 502 (e.g., a CPU), a memory 504, e.g.,random access memory (RAM) and/or read only memory (ROM), a predictionof DFI module 505, and various input/output devices 506 (e.g., storagedevices, including but not limited to, a tape drive, a floppy drive, ahard disk drive or a compact disk drive, a receiver, a transmitter, aspeaker, a display, a speech synthesizer, an output port, and a userinput device (such as but not limited to a keyboard, a keypad, a mouse,and the like)).

It should be noted that the presently disclosed subject matter can beimplemented in software and/or in a combination of software andhardware, e.g., using application specific integrated circuits (ASIC), ageneral purpose computer or any other hardware equivalents. In oneembodiment, the present prediction of DFI module or process 505 can beloaded into memory 504 and executed by processor 502 to implement thefunctions as discussed above. As such, the present prediction of DFIprocess 505 (including associated data structures) of the presentlydisclosed subject matter can be stored on a computer readable medium orcarrier, e.g., RAM memory, magnetic or optical drive or diskette and thelike.

Exemplary computer readable storage media suitable for implementing thesubject matter described herein includes disk memory devices, chipmemory devices, programmable logic devices, and application specificintegrated circuits. In some implementations, the computer readablestorage medium can include a memory accessible by a processor of acomputer or other like device. The memory can include instructionsexecutable by the processor for implementing any of the methods forpredicting DFI as described herein. In addition, a computer readablemedium that implements the subject matter described herein can belocated on a single device or computing platform or can be distributedacross multiple physical devices and/or computing platforms.

EXAMPLES

The following Examples provide illustrative embodiments. In light of thepresent disclosure and the general level of skill in the art, those ofskill will appreciate that the following Examples are intended to beexemplary only and that numerous changes, modifications, and alterationscan be employed without departing from the scope of the presentlydisclosed subject matter.

Example 1 Clones

Chromosome Region A1.

For assessment of the copy number of the chromosome region designatedherein as A1, a probe pool of four BAC clones was used. The fouroverlapping clones span a 796,156 base pair (bp) region of caninechromosome 1 (CFA1) between nucleotide 116,839,835 and nucleotide117,635,991 as set forth in the CanFam2 genome assembly (Broad Instituteof MIT/Harvard, Cambridge, Mass., United States of America) availablefrom the website of the University of Santa Cruz (Santa Cruz, Calif.,United States of America) and also disclosed as nucleotides116,839,835-117,635,991 of GENBANK® Accession No. NC_(—)006583.Evaluation of cases with copy number changes of chromosome region A1showed that the actual size of the region that presented with abnormalcopy number can extend up to the full length of the chromosome(125,616,256 bp).

In the human genome, the region that is evolutionarily conserved withCFA1 (i.e., nucleotides 116,839,835-117,635,991 of canine chromosome 1;GEN BANK® Accession No. NC_(—)006583) resides on human chromosome 19 inband q13.2. This region includes the region located at nucleotides43,452,745-44,221,900 of human chromosome 19 that includes 19q13.2 (seeGENBANK® Accession No. NC_(—)000019). These boundaries can move as thegenome is refined and so these positions represent the start and endpositions of the human chromosome that correspond to the CFA1 regions inthe dog.

Chromosome Region C2.

For assessment of the copy number of the chromosome region designatedherein as C2, a probe pool of five BAC clones was used. The fiveoverlapping clones span an 861,477 by region of canine chromosome 6(CFA6) between nucleotide 41,565,280 and nucleotide 42,426,757 as setforth in the CanFam2 genome assembly (Broad Institute of MIT/Harvard,Cambridge, Mass., United States of America) and also disclosed asnucleotides 41,565,280-42,426,757 of GENBANK® Accession No.NC_(—)006588. This region contains the gene tuberin (TSC2) that maps inthe dog at CFA6:41,934,226-41,940,068. As with chromosome region A1,evaluation of cases with copy number changes of chromosome region C2showed that the size of the region that presented with abnormal copynumber extended up to the full length of the chromosome (i.e.,80,642,250 bp).

In the human genome, the region that is evolutionarily conserved withCFA6 (i.e., 41,565,280-42,426,757 of canine chromosome 6; nucleotides41,565,280-42,426,757 of GENBANK® Accession No. NC_(—)006588) resides onhuman chromosome 16 in band p13.1. The region includes the regionlocated at nucleotides 1,629,295-2,350,975 by of human chromosome 16that includes 16p13.1 (see GENBANK® Accession No. NC_(—)000019). Theseboundaries can move as the genome is refined and so these positionsrepresent the start and end positions of the human chromosome thatcorrespond to the CFA6 regions in the dog. The tuberin gene (TSC2) inhuman maps to HSA16:2,038,617-2,036,695, and so is within this region.

The BAC clones used specifically for assessing copy number of eachregion for the development of the presently disclosed subject matter arederived from the CHORI-82 canine BAC library, details of which areavailable from the website of the Children's Hospital Oakland ResearchInstitute (Oakland, Calif., United States of America; see CHORI-82:Canine Boxer (F) (Canis familiaris) BAC Library; library identificationnumber 253) on the World Wide Web. Table 1 and show the start and endpositions in the canine genome assembly (CanFam2) for the clonesemployed herein. In addition to use of these specific canine BAC clones,any genomic DNA that hybridizes effectively and exclusively to theregions defined herein as chromosome regions A1 and C2 can be employedas suitable probes in FISH to implement the presently disclosed subjectmatter. Further, any process that allows accurate determination of meancopy number of these regions within a population of cells can be used toimplement the presently disclosed subject matter, and is thusencompassed by the present disclosure.

TABLE 1 Chromosome Region A1 (CFA 1) Evaluation with Representative,Non-limiting Four BAC Clones A1 Start End Total length of ClonesPosition* Position* Length Overlap probe pool A 116839835 117080644240810 19889 796156 B 117060755 117226554 165800 12993 C 117213561117419798 206238 9618 D 117410180 117635991 225812 *Start and EndPositions refer to nucleotide positions in the CanFam2 genome assemblyor GENBANK ® Accession No. NC_006583

TABLE 2 Chromosome Region C2 (CFA 6) Evaluation with Representative,Non-limiting Five BAC Clones C2 Start End Total length Clones Position*Position* Length Overlap of probe pool A 41565280 41750903 185624 48404861477 B 41702499 41917747 215249 75322 C 41842425 42061613 219189 66636D 41994977 42256794 261818 30789 E 42226005 42426757 200753 *Start andEnd Positions refer to nucleotide positions in the CanFam2 genomeassembly or GENBANK ® Accession No. NC_006588

Example 2 Canine Lymphoma Treatment Protocol Used for the PatientPopulation Assessed Patients

Canine patients of any breed, weight, and sex were eligible forinclusion. Dogs could not have received any prior chemotherapy. Patientshad not received any corticosteroids within the last 30 days prior tostaging. Patients did not have concurrent disease that would requiretherapy (such as diabetes), and had to have a life expectancy of atleast one year.

Patients were staged according to the World Health Organization (WHO)criteria for canine lymphoma. Evaluation included complete history andphysical exam, CBC, biochemical profile, urinalysis, chest and abdominalradiographs, bone marrow aspirate, and lymph node biopsy (in most casesexcisional).

Lymph node biopsies were obtained prior to any treatment (see FIG. 5),fixed in zinc formalin, and embedded in paraffin for routine histology.Only cancer stage 3 a and 4 a patients were included. The number ofpatients enrolled was 322.

Treatment.

Patients received doxorubicin at a dose of 30 mg/m² in 150 cc of a 0.9%NaCl infused intravenously over 20 minutes. Doxorubicin was given everythree weeks for a total of five treatments. To enhance remission status,patients also received L-asparaginase weekly for three weeks, with thefirst dose given 6-24 hours after the first dose of doxorubicin. At thetime of the 5^(th) treatment, if the patient was in remission, thepatient was randomized to receive either an investigational agent orplacebo as part of a double blind placebo controlled trial. The numberof patients in remission at the time of the 5^(th) treatment was 250.

Of the patients enrolled, 72 dogs were classified as “early failures”.These patients did not make it to investigational drug randomization.See FIG. 3. They “failed” either by coming out of remission beforetreatment Number 5 or they never went into remission. This grouprepresented dogs that had cancer that did not respond as well as wouldbe predicted.

Patient Follow Up.

The remaining patients were then followed every six weeks to assessremission status until the end of the first remission or up to twoyears, whichever came first. The follow up evaluation included aphysical exam, chest and abdominal radiographs, and blood work (CBC,biochemical profile, urinalysis).

At the end trial, there was no significant difference in the outcome ofthe two study populations (+/− investigational therapy). Thus,statistically, all dogs had received the same treatment. Detailedsignalment, including age, breed, gender, lymphoma subtype, and diseasefree interval, had been recorded for each patient. For many, theimmunophenotype of the lymphoma was also available.

Clinical disease free interval (DFI) was calculated from the time ofdiagnosis (initial visit) to time of relapse during a scheduled visit.This time period was determined by staging procedures, includinghistory, physical exam, CBC, chemistry panel, chest and abdominalradiographs, and Karnofsky's scores (Karnofsky & Burchanot (1949). Theclinical evaluation of chemotherapeutic agents. Columbia UniversityPress, New York<N.Y., United States of America). The DFI of each ofthese patients is summarized in FIG. 4.

Example 3 Scoring Archival Samples

Unlike fresh, unfixed cells, FISH analyses of formalin fixed cellstypically presents a set of technical challenges. Factors such as timefrom surgery to fixation, size of the specimen, fixation parameters andpost-fixation storage conditions can all potentially affect the qualityof FISH—especially signal to noise ratio. Formalin fixed cells generatedmuch greater background signal, and thus were not easy to interpret. SeeFIGS. 6-9.

To overcome these issues, a robust protocol that generated higher signalto noise ratio is provided herein. The protocol included modifiedpretreatment of fixed cells as well as use of longer, contiguous BACs.The use of single BACs as probes in cells derived from fixed tissuesgenerally resulted in weaker signal and with a higher background. SeeFIGS. 10D and 10E. Referring to FIG. 10, both cells in FIG. 10D and FIG.10E were fixed, but the cell in FIG. 10E was easy to score compared tothe cell in FIG. 10D due to the use of the pool of probe. To overcomethe signal to noise ratio issue in fixed cells, a series of overlappingBAC clones were selected from the genome assembly such that the totallength of the overlapping probes was approximately 800 kilobases (Kb).See Tables 1 and 2.

Ten regions selected for investigation in EXAMPLE 2 were rigorouslyevaluated in normal unfixed cells to determine probe quality and toevaluate reliability. See FIGS. 11 and 12. As is the case in humanstudies, there was a small percentage of cells that showed only one copyof the tested locus, perhaps due to spontaneous deletions and/or to theprobe being unable to access the site of the second locus within thenucleus. Counts of several hundred “normal” cells did not revealadditional copies of any of the ten loci. Copy number n=1 was seen in upto 3% of cells. Copy number n>2 was seen in 0% of cells.

In fixed nuclei, higher background noise restricted the successfulinterpretation to three to four colors, so the ten loci were evaluatedin three reactions: two containing three loci and the third containingfour probes. See FIGS. 13 and 14. As with unfixed nuclei, there was asmall percentage of cells that were deleted for one copy of probesassessed. This could have been due to spontaneous aberration in thenon-neoplastic cells and/or to the inability of the probe(s) to accessthe complimentary sequence(s) within the nuclei.

The mean copy number of chromosome region A1 was determined to bepositively associated with DFI: the higher the mean copy number, thelonger the duration of first remission and thus survival. Thisassociation can also be valid in multi-agent chemotherapy protocols. Ofparticular interest was the high proportion of cells that had threecopies (trisomy) of the loci on dog chromosomes 1 and 6. Caninechromosome 6 contains the gene TSC2, a gene involved in the regulationof cancers.

Testing Sample Population (n=121).

Initially, 121 of the 322 patient samples were selected randomly. Cellsfrom these 121 cases were evaluated initially for DNA copy number at tenloci using multicolor fluorescence in situ hybridization (FISH)protocols. For this process, a series of overlapping canine bacterialartificial chromosome (BAC) clones were identified that resided in themiddle of each of the regions each of interest. These were used in FISHassays to determine the copy number of each of the ten loci in up tofifty cells derived from each case. The mean copy number of each locuswithin each patient was then calculated and statistical analysis wasused to identify any correlation between mean DNA copy number anddisease free interval.

One probe (C4) had an unacceptable background and so was set aside forfurther development. The remaining nine (9) probes (designated as A1-A3,B1-B3, and C1-C3) were each considered for association to disease freeinterval (DFI). A regression model was developed that included potentialmultivariate risk models. Random Forests with cross-validation was usedto perform variable selection for the model, such that from the ninepotential predictor variables, only those variables that were robustpredictors were included in the final model.

The results of this first set of 121 patients indicated a significantcorrelation between mean copy number of chromosome region A1 (i.e.,canine chromosome 1; CFA1) and disease free interval. The coefficientfor the A1 mean was 334, indicating that for every 1.0 increase in copynumber, the expected value of disease free interval (DFI) increased by334 days. Univariate linear regression analysis for chromosome region A1resulted in a significant regression model associating chromosome regionA1 with DFI as follows:

DFI=333.8438×(mean copy number value for A1)−342.4995 days  Formula I

This regression explained 9.65% of the variation in DFI and the meanpredicted DFI based on various mean values for chromosome region A1 arepresented in Table 3, along with the corresponding ranges of predictedsurvival times at the 95% Confidence Interval.

TABLE 3 Prediction of Mean DFI based on Assessment of Mean Copy Numberof Chromosome Region A1 95% Confidence A1 MEAN VALUE MEAN DFI (days)Interval (days) 1.5 158.27 59.408 to 257.12 1.75 241.73 176.86 to 306.592.0 325.19 271.77 to 378.61 2.25 408.65 333.08 to 484.22 2.5 492.11379.06 to 605.16 3.0 659.03 460.16 to 857.91

The results of this first set of 121 patients also indicated asignificant correlation between mean copy number of chromosome region C2(i.e., canine chromosome 6; CFA6) and disease free interval. Thecoefficient for the chromosome region C2 mean was 253, indicating thatfor every 1.0 increase in copy number, the expected value of diseasefree interval increased by 253 days. Univariate linear regressionanalysis for chromosome region C2 resulted in a significant regressionmodel associating chromosome region C2 with DFI as follows:

DFI=253.0157×(mean copy number value for C2)−146.2368 days  Formula II

This regression explained 3.75% of the variation in DFI and the meanpredicted DFI based on various mean values for C2 are presented in Table4, along with the corresponding ranges of predicted survival times atthe 95% Confidence Interval.

TABLE 4 Prediction of Mean DFI based on Assessment of Mean Copy Numberof Chromosome Region C2 95% Confidence Interval C2 MEAN VALUE MEAN DFI(days) (days) 1.5 233.29 139.61 to 326.97 1.75 296.54 237.35 to 355.732.0 359.79 287.16 to 432.43 2.25 423.05 304.34 to 541.76 2.5 486.3313.23 to 659.38 3.0 612.81 325.04 to 900.58

Using mean copy number of the first 121 cases, two of the nine loci(chromosome regions A1 and C2) were selected as significant predictorsof outcome (chromosome region A1 was more significant than chromosomeregion C2). The tree modeling indicated a two-variable model withchromosome region A1 (CFA 1: nucleotides 116,839,835 to 117,635,991) andchromosome region C2 (CFA6: nucleotides 41,565,280 to 42,426,757) thatwas slightly more predictive than chromosome region A1 alone. Thissuggested that consideration of the mean copy number of this region ofCFA6 added to the predictive power of CFA1. Permutation testingindicated a significant two-variable model that predicted disease freeinterval, involving chromosome regions A1 and C2. The regression modeldeveloped was as follows:

DFI=327.0698×(mean copy number value for A1)+239.0605×(mean copy numbervalue for C2)−762.4566 days  Formula III

The regression equation predicted survival based on the mean copy numberof probes A1 and C2. It is possible that the slope of the regressionmight change as additional data are added, and thus the presentlydisclosed subject matter is based at least in part on identifying thestrong association between chromosome region A1 and/or chromosome regionC2 with DFI. Additional examples of prediction using the approachesdisclosed herein are provided in Table 5.

TABLE 5 Prediction of Mean DFIs Based on Assessments of Mean CopyNumbers of Chromosome Regions A1 and C2 in the Canine Genome A1 & C2MEAN DFI 95% Confidence Interval MEAN VALUE (days) (days) 1.5 90  0-2121.75 232 164-300 2.0 374 304-444 2.25 515 390-660 2.5 657 464-849 3.0941  607-1274

The data in Table 5 assumed that the mean copy numbers for bothchromosome regions A1 and C2 were the same, and this can also bemodified if either of the values were to changes. In a normal,non-cancerous dog, a copy number of 2 would be expected.

The data presented herein indicated that the mean DNA copy number ofchromosome regions A1 (CFA1) and C2 (CFA6) were able to predict diseasefree interval in dogs diagnosed with lymphoma that are receivingtherapy, as an example doxorubicin (supplemented with L-asparaginase).Since commonly employed multi-agent chemotherapy typically comprisesadministration of doxorubicin, similar results should be found in dogstreated with multi-agent chemotherapy.

Replication Sample Population (n=39).

The mean copy numbers of chromosome regions A1 and C2 were evaluated ina subsequent set of 39 additional cases (replication set) from the studypopulation. Evaluation of these 39 cases indicated a significantcorrelation between mean copy number of chromosome region A1 (La, caninechromosome 1; CFA1) and disease free interval. The significantassociation of the region defined by chromosome region A1 thus remainedin this replication set and when combined with the previous 121 cases, anew regression analysis based on all 150 cases generated Formula A, asfollows:

DFI=374.1685×(mean copy number value for A1)−438.7572 days  Formula A

This regression explained 12.08% of the variation in DFI. The meanpredicted DFI based on various mean values for chromosome region A1 arepresented in Table 6, along with the corresponding ranges of predictedsurvival times at the 95% Confidence Interval.

TABLE 6 Prediction of Mean DFI Based on Assessment of Mean Copy Numberof Chromosome Region A1 in the Canine Genome MEAN DFI 95% ConfidenceInterval A1 MEAN VALUE (days) (days) 1.5 122.5 36.505 to 208.49 1.75216.04 159.56 to 272.51 2.0 309.58 263.95 to 355.21 2.25 403.12 339.31to 466.94 2.5 496.66 400.96 to 592.37 3.0 683.75 514.55 to 852.94

Evaluation of the 39 cases comprising the replication set did notindicate a significant correlation between mean copy number ofchromosome region C2 (La, canine chromosome 6; CFA6) and disease freeinterval. The significant association of the region defined bychromosome region C2 thus did not remain evident in this replicationset. This is likely due to the small sample size of the replication set.When all 150 cases were analyzed, chromosome region C2 remained asignificant predictor of DFI.

Compilation of all data for chromosome regions A1 and C2 in all 150cases (testing set+replication set) and subsequent regression analysiswith both the chromosome region A1 and the chromosome region C2variables generated the new regression equation, Formula AC, as follows:

DFI=367.5094×(mean copy number value for A1)+228.2709×(mean copy numbervalue for C2)−839.22 days  Formula AC

This regression explained 14.52% of the variation in DFI. Tests ofsignificance indicated a highly significant association (p<0.0001) forthe chromosome region A1 variable coefficient and a significantassociation (p<0.030) for the chromosome region C2 variable coefficient.This is a nominal level of significance for chromosome region C2,indicating that it is not nearly as predictive as A1.

This equation was used to generate the mean DFI ranges of predictedsurvival times at the 95% Confidence Interval for the combined data set(see Table 7).

TABLE 7 Prediction of Mean DFI Based on Assessment of Mean Copy Numbersof Chromosome Regions A1 and C2 in the Canine Genome MEAN VALUE OF MEANDFI 95% Confidence Interval BOTH A1 and C2 (days) (days) 1.5 54.449−55.462 to 164.36  1.75 203.39 142.48 to 264.31 2.0 352.34 294.72 to409.96 2.25 501.28 396.85 to 605.72 2.5 650.23 487.52 to 812.94 3.0948.12 662.56 to 1233.7

The test, in some embodiments, is based on molecular cytogeneticevaluation of cells derived from lymph nodes of dogs diagnosed withlymphoma.

Example 4 Statistical Analyses

Univariate Screening.

Raw data for the 121 case set were collapsed into summary measures forthe nine (9) markers genotyped. The summary measures derived were asfollows: number of samples evaluated, mean copy number per sample, andproportion of samples per individual with copy number gains. Colinearitybetween markers was evaluated by examining correlations, as shown inTable 8. Significant correlations are indicated by asterisks. Theresults indicated significant correlations between chromosome regions A1and C1, as well as between chromosome regions C1 and C2.

TABLE 8 Correlation Matrix for the Nine CNV Markers Genotyped (MeanValues) A1 A2 A3 B1 B2 B3 C1 C2 A2 0.24 1.0 — — — — — A3 0.04 0.0001 1.0— — — — — B1 0.01 0.16 −0.04 1.0 — — — — B2 0.14 0.10 0.01 0.13 1.0 — —— B3 0.13 −0.15 −0.003 0.20 0.10 1.0 — — C1 0.30* 0.04 0.11 −0.13 −0.020.16 1.0 — C2 0.04 −0.10 0.13 −0.03 0.08 0.28 0.32* 1.0 C3 0.10 −0.110.20 −0.12 −0.06 0.08 0.13 0.39* Asterisks indicate significantcorrelations (p < 0.05) of mean values after Bonferroni correction formultiple testing.

Mean copy number for each marker was tested for significant correlationwith the number of samples evaluated, to evaluate potential technicalconfounding. After Bonferroni correction for multiple testing, mean copynumber of chromosome region A1 was found to be significantly correlated(p<0.001) with the number of samples collected. No other markersdemonstrated significant correlations with the number of samples. Basedon this result, significant association results were evaluated incontext of this correlation.

Univariate linear regression was performed to evaluate the associationbetween the mean copy number of each individual genetic marker and thedisease free interval. Each genetic marker was independently evaluatedin a regression model to predict the disease free interval. Table 9lists the summary statistics for the regression results for the meancopy number of each marker, based on the first 121 cases. See discussionunder “Scoring Archival Samples” in Example 3 above. After a Bonferronicorrection for multiple comparisons, marker A1 was significantlyassociated with disease free interval.

TABLE 9 R², Root Mean Square Error, and p Value for an ExemplaryRegression Model for the Mean Copy Number of Each Variant and DFIVariant R² Root Mean Square Error p value A1 0.0965 296.27 0.0005 A20.0118 317.28 0.2497 A3 0.0223 290.51 0.1077 B1 0.004 319.51 0.4851 B20.0231 295.9 0.1213 B3 0.0226 318.84 0.1337 C1 0.0031 317.81 0.5593 C20.0375 312.28 0.0390 C3 0.0033 329.72 0.5661

The univariate regression analysis was repeated using the proportion ofsamples collected per individual with copy number gains as potentialpredictors, and no results were significant at either a nominal level,or at a Bonferroni corrected level.

Predictive Modeling.

Regression trees were built, with each variant as a potential predictiveattribute (variable), weighted for the number of samples collected perindividual. Ten-fold cross-validation was used to evaluate thepredictive ability of the model, and to perform pruning (variableselection). Pruning was performed according to the following steps,based on optimizing the root mean square error of the model divided bythe global standard deviation:

-   -   1) fit a full regression model, with all potential attributes        included;    -   2) remove the attribute that contributes least to the equation        (because it has the smallest weight when the attributes are        converted to a common scale);    -   3) if the resulting equation has a lower estimated error rate,        keep the attribute out and repeat the process on the remaining        attributes, otherwise, put the attribute back in and stop the        process.

Analysis of the data from the testing set of 121 cases identified twosignificant markers, A1 and C2, that were highly significantlyassociated with DFI (p<0.0018) and in combination explained 31.06% ofthe variation in DFI.

Permutation testing was used to empirically asses the statisticalsignificance of the resulting model. This analysis indicated asignificant two-variable model that predicted disease free interval,involving chromosome regions A1 and C2. The regression model developedwas as follows:

DFI=327.0698×(mean copy number value for A1)+239.0605×(mean copy numbervalue for C2)−762.4566 days  Formula III

The summary statistics for the final model were as follows: correlationcoefficient=0.247; class complexity|order 0=708.7276 bits (5.8573bits/instance); class complexity|scheme=20722.0186 bits (171.2564bits/instance); Complexity improvement (Sf)=−20013.291 bits and=−165.3991 bits/instance. Mean absolute error=206.9582; Root meansquared error=302.8203; relative absolute error=93.9909%; root relativesquared error=97.574%.

Random Forest™.

The RANDOM FOREST™ classification and regression tool (Breiman (2001)Random Forests. Machine Learning 45(1):5-32) was investigated forpredicting a compound's quantitative or categorical biological activitybased on a quantitative description of the compound's molecularstructure. RANDOM FOREST™ is an ensemble of unpruned classification orregression trees created by using bootstrap samples of the training dataand random feature selection in tree induction. Prediction is made byaggregating (majority vote or averaging) the predictions of theensemble. RANDOM FOREST™ is a tool capable of delivering performancethat is among the most accurate methods to date.

Replication.

In order to further evaluate this model, a replication set of data(n=29) was collected to test the predictive power of these two markersin an independent, separate sample. In the replication sample,chromosome region A1 remained highly significantly associated withsurvival outcome (p<0.002), but chromosome region C2 was not (p>0.05),likely due to much lower sample size and lower power of this locus.These data demonstrated the highly robust nature of chromosome region A1as a predictor of response to therapy.

Data from this second set of 29 patients independently also revealed astrong association between the mean copy number of chromosome region A1and DFI. By combining all cases evaluated to date the total number is150 and analysis of chromosome region A1 in this larger cohort generatedthe regression as shown below.

The overall regression model was still significant with the coefficientfor chromosome region A1 mean significant at p<0.0001. The revisedsignificant regression model associating chromosome region A1, based onall 150 cases (see Example 3, Table 6 above), was as follows:

DFI=374.1685×(mean copy number value for A1)−438.7572 days  Formula A

The coefficient for the A1 mean was 374.1685, indicating that for every1.0 increase in copy number, the expected value of disease free intervalincreased by 374.1685 days.

Table 10 provides a prediction of mean disease free intervals (days) andthe ranges associated with the 95% Confidence Intervals, based on anassessment of the mean copy number of chromosome region A1 in the caninegenome, using the combined (n=150) dataset (original (n=121) plus thereplication (n=29)) samples considering only the chromosome region A1variable. The regression equation used to generate the data presented inTable 10 was Formula A as follows:

DFI=374.1685×(mean copy number value for A1)−438.7572 days  Formula A

TABLE 10 Prediction of Mean DFI Based on Assessment of Mean Copy Numberof Chromosome Region A1 in the Canine Genome in the Combined Data SetMEAN DFI A1 MEAN VALUE (days) 95% Confidence Interval (days) 1.5 122.536.505 to 208.49 1.75 216.04 159.56 to 272.51 2.0 309.58 263.95 to355.21 2.25 403.12 339.31 to 466.94 2.5 496.66 400.96 to 592.37 3.0683.75 514.55 to 852.94

The regression data presented in Table 10 explained 12.08% of thevariation in DFI.

Regression analysis on only the C2 variable using the combined dataset(n=150 patients), generated the following revised regression equation(p<0.014):

DFI=271.4727×(mean copy number value for C2)−199.6737 days  Formula C

This regression explained 4.01% of the variation in DFI.

Combining data for chromosome regions A1 and C2 for all 150 casesgenerated the following regression (Formula AC) when both regions wereconsidered.

DFI=367.50949×(mean copy number value for A1)+228.2709×(mean copy numbervalue for C2)−839.22 days  Formula AC

This regression explained 14.52% of the variation in DFI. Tests ofsignificance indicated p<0.0001 for the A1 variable coefficient andp<0.030 for the C2 variable coefficient. While this is a nominal levelof significance for C2, C2 was not as predictive as A1. Examples of meanDFI and corresponding values at 95% Confidence Interval are shown inTable 11, assuming the values for mean A1 and mean C2 are the same.

TABLE 11 Prediction of Mean DFI Based on Assessment of Mean Copy Numberof Chromosome Regions A1 and C2 in the Canine Genome in the CombinedData Set MEAN VALUE OF BOTH A1 MEAN DISEASE FREE 95% Confidence Intervaland C2 INTERVAL (days) (days) 1.5 54.449 −55.462 to 164.36  1.75 203.39142.48 to 264.31 2.0 352.34 294.72 to 409.96 2.25 501.28 396.85 to605.72 2.5 650.23 487.52 to 812.94 3.0 948.12 662.56 to 1233.7

It will be understood that various details of the presently disclosedsubject matter may be changed without departing from the scope of thepresently disclosed subject matter. Furthermore, the foregoingdescription is for the purpose of illustration only, and not for thepurpose of limitation.

1. A method for predicting the disease free time interval for a subjectwith a cancer under consideration for initial or further chemotherapytreatment, the method comprising: obtaining a biological sample from thesubject, wherein the sample comprises a number of cells; detecting acopy number of chromosome region A1 in the biological sample; dividingthe copy number by the number of cells in the biological sample toobtain a mean copy number value for A1; and correlating the mean copynumber value with a risk of relapse; wherein the correlating predictsthe disease free interval for the subject.
 2. The method of claim 1,wherein the subject has lymphoma.
 3. The method of claim 2, wherein thelymphoma is non-Hodgkin's lymphoma.
 4. The method of claim 1, whereinthe subject is a canine.
 5. The method of claim 1, wherein thebiological sample comprises a biopsy.
 6. The method of claim 1, whereinthe biological sample comprises lymph node cells.
 7. The method of claim1, wherein the chemotherapy treatment comprises administeringdoxorubicin to the subject.
 8. The method of claim 7, wherein thechemotherapy treatment further comprises administering L-asparaginase tothe subject.
 9. The method of claim 1, wherein the detecting a copynumber of A1 comprises contacting the sample with one or more probesable to detect the presence of chromosome region A1 under conditionssufficient to enable hybridization of the probe to chromosome region A1.10. The method of claim 9, wherein the one or more probes arefluorescently labeled.
 11. The method of claim 9, wherein the contactingthe sample comprises fluorescence in situ hybridization analysis. 12.The method of claim 9, wherein the contacting the sample comprisespolymerase chain reaction. analysis
 13. The method of claim 1, furthercomprising determining the disease free interval (DFI) by substitutingthe mean copy number value for A1 into Formula A, wherein Formula A is:DFI=374.1685×(mean copy number value for A1)−438.7572 days
 14. Themethod of claim 1, further comprising: detecting a copy number ofchromosome region C2 in the biological sample; and dividing the copynumber by the number of cells in the biological sample to obtain a meancopy number value for C2.
 15. The method of claim 14, wherein thedetecting a copy number of chromosome region C2 comprises contacting thesample with a probe able to detect the presence of chromosome region C2under conditions sufficient to enable hybridization of the probe tochromosome region C2.
 16. The method of claim 14, further comprisingdetermining the disease free interval (DFI) by substituting the meancopy number value for A1 and the mean copy number value for C2 intoFormula AC, wherein Formula AC is:DFI=367.5094×(mean copy number value for A1)+228.2709×(mean copy numbervalue for C2)−839.22 days
 17. The method of claim 1, wherein a mean copynumber has a positive correlation with an increased disease free timeinterval.
 18. A kit for predicting disease free time interval in asubject with cancer under consideration for initial or furtherchemotherapy treatment, the kit comprising a probe able to detectchromosome region A1 in a biological sample isolated from the subjectwith cancer.
 19. The kit of claim 18, further comprising a probe able todetect chromosome region C2 in a biological sample isolated from thesubject with cancer.
 20. A computer readable storage medium havingstored thereon computer executable instructions that when executed by aprocessor of a computer control the computer to perform stepscomprising: analyzing a mean copy number from chromosome region A1 froma biological sample obtained from a subject with a cancer; andoutputting a predicted disease free interval (DFI) for the subject. 21.The computer readable storage medium of claim 20, wherein the processoremploys Formula A to compute the DFI, and further wherein Formula A is:DFI=374.1685×(mean copy number value for A1)−438.7572 days.
 22. Thecomputer readable storage medium of claim 20, further comprisinginstructions that control the computer to perform steps comprisinganalyzing a mean copy number from chromosome region C2 from thebiological sample.
 23. The computer readable storage medium of claim 22,wherein the processor employs Formula AC to compute the DFI, and furtherwherein Formula AC is:DFI=367.5094×(mean copy number value for A1)+228.2709×(mean copy numbervalue for C2)−839.22 days.